Two important questions are addressed in this paper using the Global Ensemble Forecast System (GEFS) from the National Centers for Environmental Prediction (NCEP): (1) How many ensemble members are needed to be...Two important questions are addressed in this paper using the Global Ensemble Forecast System (GEFS) from the National Centers for Environmental Prediction (NCEP): (1) How many ensemble members are needed to better represent forecast uncertainties with limited computational resources? (2) What is tile relative impact on forecast skill of increasing model resolution and ensemble size? Two-month experiments at T126L28 resolution were used to test the impact of varying the ensemble size from 5 to 80 members at the 500- hPa geopotential height. Results indicate that increasing the ensemble size leads to significant improvements in the performance for all forecast ranges when measured by probabilistic metrics, but these improvements are not significant beyond 20 members for long forecast ranges when measured by deterministic metrics. An ensemble of 20 to 30 members is the most effective configuration of ensemble sizes by quantifying the tradeoff between ensemble performance and the cost of computational resources. Two representative configurations of the GEFS the T126L28 model with 70 members and the T190L28 model with 20 members, which have equivalent computing costs--were compared. Results confirm that, for the NCEP GEFS, increasing the model resolution is more (less) beneficial than increasing the ensemble size for a short (long) forecast range.展开更多
The influences of Tropical Rainfall Measuring Mission (TRMM) precipitation products on the structure and underlying physics of intraseasonal oscillation (ISO) are investigated with the U.S.National Aeronautics and Spa...The influences of Tropical Rainfall Measuring Mission (TRMM) precipitation products on the structure and underlying physics of intraseasonal oscillation (ISO) are investigated with the U.S.National Aeronautics and Space Administration Goddard Earth Observing System model version 3 (GEOS-3) data assimilation system (DAS).The strong ISO phase in the 1998 summer is apparently located in the Asian monsoon region and the east equatorial Pacific region.The eastward propagation is a dominant feature for the tropical ISO at 20 to 30-day oscillation while the northeastward propagation is the salient ISO at 30 to 60-day oscillation over the 10°N to 25°N belt region.It appears that the Kelvin wave structure is for the tropical 20 to 30-day oscillation.The tropical 30 to 60-day oscillation has the characteristics of the Kelvin-Rossby wave.The impact of satellite-derived precipitation (and its associated latent heating) on the ISO intensity is limited in the GEOS-3 assimilation system.However,its impact on the ISO spatial structures is obvious.Overall,the results demonstrate a better eastward propagation and a northward propagation of ISO with the TRMM precipitation simulation,indicating that latent heating is very important in exciting the equatorial ISO.展开更多
This study shows that the heretofore assumed condition for no temperature-profile (TP)/lapse-rate feedback, for all altitudes z, or , in fact yields a negative feedback. The correct condition for no TP feedback is for...This study shows that the heretofore assumed condition for no temperature-profile (TP)/lapse-rate feedback, for all altitudes z, or , in fact yields a negative feedback. The correct condition for no TP feedback is for all z, where Ts is the surface temperature. This condition translates into a uniform increase (decrease) in lapse rate with altitude for an increase (decrease) in Ts. The temperature changes caused by a change in solar irradiance and/or planetary albedo satisfy the condition for no TP feedback. The temperature changes caused by a change in greenhouse gas concentration do not satisfy the condition for no TP feedback and, instead, yield a positive feedback.展开更多
The diurnal variability of precipitation depth over the Tibetan Plateau and its surrounding regions is investigated using nine years of Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) measureme...The diurnal variability of precipitation depth over the Tibetan Plateau and its surrounding regions is investigated using nine years of Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) measurements. The Tibetan Plateau, the plains area, and the East China Sea are selected as the focus regions in this study. The average precipitation depths (PD) are about 4.6 km, 5.8 km, and 5.6 km, while convective (stratiform) PDs are about 6.6 (4.5) km, 7.5 (5.7) km, and 6.0 (5.6) km over the plateau, the plains, and the ocean region, respectively. Results demonstrate a prominent PD diurnal cycle, and its diurnal phase is generally a few hours behind the surface precipitation. The spatial variation of the PD diurnal magnitude is weaker near the coastal areas than that of surface precipitation. The height of the PD diurnal peak is around 6 7 km for convective systems and 5-6 km for stratifrom systems. The dominant afternoon diurnal peak for convective PD and the flat diurnal peak for stratiform PD over the Tibetan Plateau indicate that solar diurnal forcing is the key mechanism of the PD diurnal cycle over land. In addition, the diurnal variation is obvious for shallow and deep convective systems, but not for shallow and deep stratiform systems.展开更多
Since the North American and Global Land Data Assimilation Systems(NLDAS and GLDAS) were established in2004, significant progress has been made in development of regional and global LDASs. National, regional, projectb...Since the North American and Global Land Data Assimilation Systems(NLDAS and GLDAS) were established in2004, significant progress has been made in development of regional and global LDASs. National, regional, projectbased, and global LDASs are widely developed across the world. This paper summarizes and overviews the development, current status, applications, challenges, and future prospects of these LDASs. We first introduce various regional and global LDASs including their development history and innovations, and then discuss the evaluation, validation, and applications(from numerical model prediction to water resources management) of these LDASs. More importantly, we document in detail some specific challenges that the LDASs are facing: quality of the in-situ observations, satellite retrievals, reanalysis data, surface meteorological forcing data, and soil and vegetation databases; land surface model physical process treatment and parameter calibration; land data assimilation difficulties; and spatial scale incompatibility problems. Finally, some prospects such as the use of land information system software, the unified global LDAS system with nesting concept and hyper-resolution, and uncertainty estimates for model structure,parameters, and forcing are discussed.展开更多
The North American Soil Moisture Database (NASMD) was initiated in 2011 to assemble and homogenize in situ soil moisture measurements from 32 observational networks in the United States and Canada encompassing more th...The North American Soil Moisture Database (NASMD) was initiated in 2011 to assemble and homogenize in situ soil moisture measurements from 32 observational networks in the United States and Canada encompassing more than 1800 stations. Although statistical quality control (QC) procedures have been applied in the NASMD, the soil moisture content tends to be systematically underestimated by in situ sensors in frozen soils, and using a single maximum threshold (i.e., 0.6 m3 m-3) may not be sufficient for robust QC because of the diverse soil textures in North America. In this study, based on the in situ soil porosity and North American Land Data Assimilation System phase 2 (NLDAS-2) Noah soil temperature, the simple automated QC method is revised to supplement the existing QC approach. This revised QC method is first validated based on the assessment at 78 of the Soil Climate Analysis Network (SCAN) stations where the manually checked data are available, and is then applied to all stations in the NASMD to produce a more strict quality-controlled dataset. The results show that the revised automated QC procedure can flag the spurious and erroneous soil moisture measurements for the SCAN stations, especially for those located in high altitudes and latitudes. Relative to station measurements in the original NASMD, the quality-controlled data show a slightly better agreement with the manually checked soil moisture content. It should be noted that this quality-controlled dataset may be over-flagged for some valid soil moisture measurements due to potential errors of the soil temperature and soil porosity data, and validation in this study is limited by the availability of benchmark soil moisture data. The updated QC and additional validation will be desirable to boost confidence in the product when high-quality data become available in the future.展开更多
The Advanced Microwave Sounding Unit-A(AMSU-A) onboard the NOAA satellites NOAA-18 and NOAA-19 and the European Organization for the Exploitation of Meteorological Satellites(EUMETSAT)Met Op-A, the hyperspectral A...The Advanced Microwave Sounding Unit-A(AMSU-A) onboard the NOAA satellites NOAA-18 and NOAA-19 and the European Organization for the Exploitation of Meteorological Satellites(EUMETSAT)Met Op-A, the hyperspectral Atmospheric Infrared Sounder(AIRS) onboard Aqua, the High resolution Infra Red Sounder(HIRS) onboard NOAA-19 and Met Op-A, and the Advanced Technology Microwave Sounder(ATMS) onboard Suomi National Polar-orbiting Partnership(NPP) satellite provide upper-level sounding channels in tropical cyclone environments. Assimilation of these upper-level sounding channels data in the Hurricane Weather Research and Forecasting(HWRF) system with two different model tops is investigated for the tropical storms Debby and Beryl and hurricanes Sandy and Isaac that occurred in 2012. It is shown that the HWRF system with a higher model top allows more upper-level microwave and infrared sounding channels data to be assimilated into HWRF due to a more accurate upper-level background profile. The track and intensity forecasts produced by the HWRF data assimilation and forecast system with a higher model top are more accurate than those with a lower model top.展开更多
This study presents the real-time performance of the United States(US) National Centers for Environmental Prediction(NCEP) operational Hurricane Weather Research and Forecast(HWRF) model in predicting rapid intensific...This study presents the real-time performance of the United States(US) National Centers for Environmental Prediction(NCEP) operational Hurricane Weather Research and Forecast(HWRF) model in predicting rapid intensification(RI) of typhoons in the North Western Pacific(WPAC) basin in 2013. Examination of all RI cases in WPAC during 2013 shows that the HWRF model captures a consistent vortex structure at the onset of all RI as seen in previous idealized studies with HWRF. However, HWRF has issues with predicting RI when the model vortex is initialized with intensity greater than hurricane strength. Further verification of the probability of detection(POD) and the false alarm rate(FAR) of RI forecasts shows that the HWRF model outperforms all other models used by the US Navy’s Joint Typhoon Warning Center, possessing highest POD and lowest FAR in 2013. Examination of the intensity change forecasts at different forecast lead times also confirms that the HWRF model has superior performance, particularly at the 72-h lead time with the POD index ~0.91 and the FAR index ~0.33. Such unique performance of the HWRF model demonstrates its role in helping operational agencies improve their official intensity(and RI) forecasts for tropical cyclones in the WPAC basin.展开更多
This paper proposes a method for multi-model ensemble forecasting based on Bayesian model averaging (BMA), aiming to improve the accuracy of tropical cyclone (TC) intensity forecasts, especially forecasts of minim...This paper proposes a method for multi-model ensemble forecasting based on Bayesian model averaging (BMA), aiming to improve the accuracy of tropical cyclone (TC) intensity forecasts, especially forecasts of minimum surface pressure at the cyclone center (Pmin)' The multi-model ensemble comprises three operational forecast models: the Global Forecast System (GFS) of NCEP, the Hurricane Weather Research and Forecasting (HWRF) models of NCEP, and the Integrated Forecasting System (IFS) of ECMWF. The mean of a predictive distribution is taken as the BMA forecast. In this investigation, bias correction of the minimum surface pressure was applied at each forecast lead time, and the distribution (or probability density function, PDF) of emin was used and transformed. Based on summer season forecasts for three years, we found that the intensity errors in TC forecast from the three models var-ied significantly. The HWRF had a much smaller intensity error for short lead-time forecasts. To demonstrate the proposed methodology, cross validation was implemented to ensure more efficient use of the sample data and more reliable testing. Comparative analysis shows that BMA for this three-model ensemble, after bias correction and distri-bution transformation, provided more accurate forecasts than did the best of the ensemble members (HWRF), with a 5%-7% decrease in root-mean-square error on average. BMA also outperformed the multi-model ensemble, and it produced "predictive variance" that represented the forecast uncertainty of the member models. In a word, the BMA method used in the multi-model ensemble forecasting was successful in TC intensity forecasts, and it has the poten-tial to be applied to routine operational forecasting.展开更多
The tropical cyclone(TC)named Amos(2016)that impacted the Samoan Islands on 23 April 2016 was a particularly dif f icult storm to forecast.Both the intensity changes and the track of Amos represent a signif icant chal...The tropical cyclone(TC)named Amos(2016)that impacted the Samoan Islands on 23 April 2016 was a particularly dif f icult storm to forecast.Both the intensity changes and the track of Amos represent a signif icant challenge for forecasters and this is briefl y summarized in this report.Model forecasts initially indicated that the cyclone would track south of the Samoan Islands.However,the forecasts generally changed to a direct hit over Samoa as a Category 4 storm at approximately 0000 U TC 24April based on model cycles initialized at 0000 UTC 23 April.TC Amos’central pressure dropped from 983 hPa to 957 hPa between 0000 UTC 21 April and 0000 UTC 23April.The models did not pick up on this rapid intensif ication until the intensif ication had already begun around0000 UTC 21 April.The models also struggled to capture the rapid weakening of TC Amos due to vertical wind shear that began 0000 UTC 24 April as the cyclone continued to move north of the islands.Because of the initially ominous track forecasts for TC Amos to hit land,preparations for a Category 3 or Category 4 cyclone were underway in the Samoan islands and the population prepared for the worst.After the center of the storm moved north of the islands as a weaker storm than anticipated,the residents of the Samoan Islands were both surprised and relieved that the cyclone only gave a"glancing blow"to the islands and that the impacts were not as bad as originally feared.An in-depth evaluation of this particular tropical cyclone helps to shed some light on model def iciencies and can be used to help determine future model changes.展开更多
文摘Two important questions are addressed in this paper using the Global Ensemble Forecast System (GEFS) from the National Centers for Environmental Prediction (NCEP): (1) How many ensemble members are needed to better represent forecast uncertainties with limited computational resources? (2) What is tile relative impact on forecast skill of increasing model resolution and ensemble size? Two-month experiments at T126L28 resolution were used to test the impact of varying the ensemble size from 5 to 80 members at the 500- hPa geopotential height. Results indicate that increasing the ensemble size leads to significant improvements in the performance for all forecast ranges when measured by probabilistic metrics, but these improvements are not significant beyond 20 members for long forecast ranges when measured by deterministic metrics. An ensemble of 20 to 30 members is the most effective configuration of ensemble sizes by quantifying the tradeoff between ensemble performance and the cost of computational resources. Two representative configurations of the GEFS the T126L28 model with 70 members and the T190L28 model with 20 members, which have equivalent computing costs--were compared. Results confirm that, for the NCEP GEFS, increasing the model resolution is more (less) beneficial than increasing the ensemble size for a short (long) forecast range.
基金Qing Lan Project and a Special Public Sector Research (GYHY200806009)The second author was funded by the NASA Global Water and Energy Cycle project with a grant NNG04G098G
文摘The influences of Tropical Rainfall Measuring Mission (TRMM) precipitation products on the structure and underlying physics of intraseasonal oscillation (ISO) are investigated with the U.S.National Aeronautics and Space Administration Goddard Earth Observing System model version 3 (GEOS-3) data assimilation system (DAS).The strong ISO phase in the 1998 summer is apparently located in the Asian monsoon region and the east equatorial Pacific region.The eastward propagation is a dominant feature for the tropical ISO at 20 to 30-day oscillation while the northeastward propagation is the salient ISO at 30 to 60-day oscillation over the 10°N to 25°N belt region.It appears that the Kelvin wave structure is for the tropical 20 to 30-day oscillation.The tropical 30 to 60-day oscillation has the characteristics of the Kelvin-Rossby wave.The impact of satellite-derived precipitation (and its associated latent heating) on the ISO intensity is limited in the GEOS-3 assimilation system.However,its impact on the ISO spatial structures is obvious.Overall,the results demonstrate a better eastward propagation and a northward propagation of ISO with the TRMM precipitation simulation,indicating that latent heating is very important in exciting the equatorial ISO.
文摘This study shows that the heretofore assumed condition for no temperature-profile (TP)/lapse-rate feedback, for all altitudes z, or , in fact yields a negative feedback. The correct condition for no TP feedback is for all z, where Ts is the surface temperature. This condition translates into a uniform increase (decrease) in lapse rate with altitude for an increase (decrease) in Ts. The temperature changes caused by a change in solar irradiance and/or planetary albedo satisfy the condition for no TP feedback. The temperature changes caused by a change in greenhouse gas concentration do not satisfy the condition for no TP feedback and, instead, yield a positive feedback.
基金supportedby the National Natural Science Foundation of China with research Grant Nos.40428002,40633018,and 40775058
文摘The diurnal variability of precipitation depth over the Tibetan Plateau and its surrounding regions is investigated using nine years of Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) measurements. The Tibetan Plateau, the plains area, and the East China Sea are selected as the focus regions in this study. The average precipitation depths (PD) are about 4.6 km, 5.8 km, and 5.6 km, while convective (stratiform) PDs are about 6.6 (4.5) km, 7.5 (5.7) km, and 6.0 (5.6) km over the plateau, the plains, and the ocean region, respectively. Results demonstrate a prominent PD diurnal cycle, and its diurnal phase is generally a few hours behind the surface precipitation. The spatial variation of the PD diurnal magnitude is weaker near the coastal areas than that of surface precipitation. The height of the PD diurnal peak is around 6 7 km for convective systems and 5-6 km for stratifrom systems. The dominant afternoon diurnal peak for convective PD and the flat diurnal peak for stratiform PD over the Tibetan Plateau indicate that solar diurnal forcing is the key mechanism of the PD diurnal cycle over land. In addition, the diurnal variation is obvious for shallow and deep convective systems, but not for shallow and deep stratiform systems.
基金Supported by the US Environmental Modeling Center(EMC)Land Surface Modeling Project(granted to Youlong Xia)National Natural Science Foundation of China(51609111,granted to Baoqing Zhang)
文摘Since the North American and Global Land Data Assimilation Systems(NLDAS and GLDAS) were established in2004, significant progress has been made in development of regional and global LDASs. National, regional, projectbased, and global LDASs are widely developed across the world. This paper summarizes and overviews the development, current status, applications, challenges, and future prospects of these LDASs. We first introduce various regional and global LDASs including their development history and innovations, and then discuss the evaluation, validation, and applications(from numerical model prediction to water resources management) of these LDASs. More importantly, we document in detail some specific challenges that the LDASs are facing: quality of the in-situ observations, satellite retrievals, reanalysis data, surface meteorological forcing data, and soil and vegetation databases; land surface model physical process treatment and parameter calibration; land data assimilation difficulties; and spatial scale incompatibility problems. Finally, some prospects such as the use of land information system software, the unified global LDAS system with nesting concept and hyper-resolution, and uncertainty estimates for model structure,parameters, and forcing are discussed.
基金Supported by the National Key Research and Development Program of China(2017YFA0604300)National Natural Science Foundation of China(51779278,51379224,and 41671398)NOAA/CPO Modeling,Analyses,Predictions,and Projections(MAP) Program
文摘The North American Soil Moisture Database (NASMD) was initiated in 2011 to assemble and homogenize in situ soil moisture measurements from 32 observational networks in the United States and Canada encompassing more than 1800 stations. Although statistical quality control (QC) procedures have been applied in the NASMD, the soil moisture content tends to be systematically underestimated by in situ sensors in frozen soils, and using a single maximum threshold (i.e., 0.6 m3 m-3) may not be sufficient for robust QC because of the diverse soil textures in North America. In this study, based on the in situ soil porosity and North American Land Data Assimilation System phase 2 (NLDAS-2) Noah soil temperature, the simple automated QC method is revised to supplement the existing QC approach. This revised QC method is first validated based on the assessment at 78 of the Soil Climate Analysis Network (SCAN) stations where the manually checked data are available, and is then applied to all stations in the NASMD to produce a more strict quality-controlled dataset. The results show that the revised automated QC procedure can flag the spurious and erroneous soil moisture measurements for the SCAN stations, especially for those located in high altitudes and latitudes. Relative to station measurements in the original NASMD, the quality-controlled data show a slightly better agreement with the manually checked soil moisture content. It should be noted that this quality-controlled dataset may be over-flagged for some valid soil moisture measurements due to potential errors of the soil temperature and soil porosity data, and validation in this study is limited by the availability of benchmark soil moisture data. The updated QC and additional validation will be desirable to boost confidence in the product when high-quality data become available in the future.
基金Supported by the NOAA Hurricane Forecast Improvement Program(HFIP)National Natural Science Foundation of China(91337218)
文摘The Advanced Microwave Sounding Unit-A(AMSU-A) onboard the NOAA satellites NOAA-18 and NOAA-19 and the European Organization for the Exploitation of Meteorological Satellites(EUMETSAT)Met Op-A, the hyperspectral Atmospheric Infrared Sounder(AIRS) onboard Aqua, the High resolution Infra Red Sounder(HIRS) onboard NOAA-19 and Met Op-A, and the Advanced Technology Microwave Sounder(ATMS) onboard Suomi National Polar-orbiting Partnership(NPP) satellite provide upper-level sounding channels in tropical cyclone environments. Assimilation of these upper-level sounding channels data in the Hurricane Weather Research and Forecasting(HWRF) system with two different model tops is investigated for the tropical storms Debby and Beryl and hurricanes Sandy and Isaac that occurred in 2012. It is shown that the HWRF system with a higher model top allows more upper-level microwave and infrared sounding channels data to be assimilated into HWRF due to a more accurate upper-level background profile. The track and intensity forecasts produced by the HWRF data assimilation and forecast system with a higher model top are more accurate than those with a lower model top.
文摘This study presents the real-time performance of the United States(US) National Centers for Environmental Prediction(NCEP) operational Hurricane Weather Research and Forecast(HWRF) model in predicting rapid intensification(RI) of typhoons in the North Western Pacific(WPAC) basin in 2013. Examination of all RI cases in WPAC during 2013 shows that the HWRF model captures a consistent vortex structure at the onset of all RI as seen in previous idealized studies with HWRF. However, HWRF has issues with predicting RI when the model vortex is initialized with intensity greater than hurricane strength. Further verification of the probability of detection(POD) and the false alarm rate(FAR) of RI forecasts shows that the HWRF model outperforms all other models used by the US Navy’s Joint Typhoon Warning Center, possessing highest POD and lowest FAR in 2013. Examination of the intensity change forecasts at different forecast lead times also confirms that the HWRF model has superior performance, particularly at the 72-h lead time with the POD index ~0.91 and the FAR index ~0.33. Such unique performance of the HWRF model demonstrates its role in helping operational agencies improve their official intensity(and RI) forecasts for tropical cyclones in the WPAC basin.
基金Supported by the National Natural Science Foundation of China(40830957)China Meteorological Administration Special Public Welfare Research Fund(GYHY201106018)+2 种基金National Basic Research and Development(973)Program of China(2011CB421504)National Science and Technology Support Program of China(2010BAC51B05)Knowledge Innovation Project of the Chinese Academy of Sciences(KZCX2-YW-Q1-02)
文摘This paper proposes a method for multi-model ensemble forecasting based on Bayesian model averaging (BMA), aiming to improve the accuracy of tropical cyclone (TC) intensity forecasts, especially forecasts of minimum surface pressure at the cyclone center (Pmin)' The multi-model ensemble comprises three operational forecast models: the Global Forecast System (GFS) of NCEP, the Hurricane Weather Research and Forecasting (HWRF) models of NCEP, and the Integrated Forecasting System (IFS) of ECMWF. The mean of a predictive distribution is taken as the BMA forecast. In this investigation, bias correction of the minimum surface pressure was applied at each forecast lead time, and the distribution (or probability density function, PDF) of emin was used and transformed. Based on summer season forecasts for three years, we found that the intensity errors in TC forecast from the three models var-ied significantly. The HWRF had a much smaller intensity error for short lead-time forecasts. To demonstrate the proposed methodology, cross validation was implemented to ensure more efficient use of the sample data and more reliable testing. Comparative analysis shows that BMA for this three-model ensemble, after bias correction and distri-bution transformation, provided more accurate forecasts than did the best of the ensemble members (HWRF), with a 5%-7% decrease in root-mean-square error on average. BMA also outperformed the multi-model ensemble, and it produced "predictive variance" that represented the forecast uncertainty of the member models. In a word, the BMA method used in the multi-model ensemble forecasting was successful in TC intensity forecasts, and it has the poten-tial to be applied to routine operational forecasting.
文摘The tropical cyclone(TC)named Amos(2016)that impacted the Samoan Islands on 23 April 2016 was a particularly dif f icult storm to forecast.Both the intensity changes and the track of Amos represent a signif icant challenge for forecasters and this is briefl y summarized in this report.Model forecasts initially indicated that the cyclone would track south of the Samoan Islands.However,the forecasts generally changed to a direct hit over Samoa as a Category 4 storm at approximately 0000 U TC 24April based on model cycles initialized at 0000 UTC 23 April.TC Amos’central pressure dropped from 983 hPa to 957 hPa between 0000 UTC 21 April and 0000 UTC 23April.The models did not pick up on this rapid intensif ication until the intensif ication had already begun around0000 UTC 21 April.The models also struggled to capture the rapid weakening of TC Amos due to vertical wind shear that began 0000 UTC 24 April as the cyclone continued to move north of the islands.Because of the initially ominous track forecasts for TC Amos to hit land,preparations for a Category 3 or Category 4 cyclone were underway in the Samoan islands and the population prepared for the worst.After the center of the storm moved north of the islands as a weaker storm than anticipated,the residents of the Samoan Islands were both surprised and relieved that the cyclone only gave a"glancing blow"to the islands and that the impacts were not as bad as originally feared.An in-depth evaluation of this particular tropical cyclone helps to shed some light on model def iciencies and can be used to help determine future model changes.